%matplotlib inline
import matplotlib.pyplot as plt
import plotly
plotly.offline.init_notebook_mode()
import os
import numpy as np
from scipy.io import wavfile
import plotly.graph_objs as go
from plotly.offline import iplot
import random
from os import listdir
from os.path import isfile, join
import subprocess
from plotly import tools
import plotly.plotly as py
mypath = 'validation'
onlyfiles = [f for f in listdir(mypath) if isfile(join(mypath, f))]
random.shuffle(onlyfiles)
subprocess.call(["python", "generate.py", '--wav_out_path=conditionedSamples/generated_1.wav', '--samples', '9000', '--wav_seed=validation/A05088.wav', 'logdir_normal_nosilence/train/Checkpoint/model.ckpt-19999'])
myFiles = onlyfiles[:10]
data = wavfile.read('validation/'+myFiles[0])[1]
for x in myFiles:
data = wavfile.read('validation/'+x)[1]
iplot([go.Scatter(x=np.arange(len(data))/300.0, y=data)])
for x in myFiles:
subprocess.call(["python", "generate.py", '--wav_out_path=conditionedSamples/generated'+x, '--samples', '9000', '--wav_seed=validation/'+x, 'logdir_normal_nosilence/train/Checkpoint/model.ckpt-19999'])
rate,data = wavfile.read('conditionedSamples/generated'+x)
iplot([go.Scatter(x=np.arange(len(data))/300.0, y=data)])
myFiles
i = 0
for x in myFiles:
rate,data = wavfile.read('conditionedSamples/generated'+x)
original = data[0:8000]
rest = data[8000:]
org = go.Scatter(x=np.arange(len(original))/300.0, y=np.abs(np.fft.fft(original)))
gen = go.Scatter(x=np.arange(len(rest))/300.0, y=np.abs(np.fft.fft(rest)))
fig = tools.make_subplots(rows=1, cols=2)
fig.append_trace(org, 1, 1)
fig.append_trace(gen, 1, 2)
iplot(fig)
for x in myFiles:
rate,data = wavfile.read('conditionedSamples/generated'+x)
original = data[0:8000]
rest = data[8000:]
orgmean = np.mean(original)
orgrest = np.mean(rest)
print("Mean of the original sample for file " + x + " was ", orgmean, "while for the generated portion it was ", orgrest)